Predicting Western Pacific Subtropical High Using a Combined Tropical Indian Ocean Sea Surface Temperature Forecast

被引:5
|
作者
Wang Li-Wei [1 ,2 ,3 ]
Zheng Fei [1 ]
Zhu, Jiang [1 ]
机构
[1] Chinese Acad Sci, ICCES, Inst Atmospher Phys, Beijing 100029, Peoples R China
[2] Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
[3] Beijing Inst Appl Meteorol, Beijing 100029, Peoples R China
基金
中国国家自然科学基金;
关键词
western Pacific subtropical high; SST; tropical Indian Ocean; statistical prediction;
D O I
10.3878/j.issn.1674-2834.13.0030
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Weather and climate in East China are closely related to the variability of the western Pacific subtropical high (WPSH), which is an important part of the Asian monsoon system. The WPSH prediction in spring and summer is a critical component of rainfall forecasting during the summer flood season in China. Although many attempts have been made to predict WPSH variability, its predictability remains limited in practice due to the complexity of the WPSH evolution. Many studies have indicated that the sea surface temperature (SST) over the tropical Indian Ocean has a significant effect on WPSH variability. In this paper, a statistical model is developed to forecast the monthly variation in the WPSH during the spring and summer seasons on the basis of its relationship with SST over the tropical Indian Ocean. The forecasted SST over the tropical Indian Ocean is the predictor in this model, which differs significantly from other WPSH prediction methods. A 26-year independent hindcast experiment from 1983 to 2008 is conducted and validated in which the WPSH prediction driven by the combined forecasted SST is compared with that driven by the persisted SST. Results indicate that the skill score of the WPSH prediction driven by the combined forecasted SST is substantial.
引用
收藏
页码:405 / 409
页数:5
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